Poor-prognosis estrogen receptor-positive breast cancer identified by histopathologic subclassification.
OBJECTIVE
Identification of biologically and clinically distinct breast cancer subtypes could improve prognostic assessment of primary tumors. The characteristics of "molecular" breast cancer subtypes suggest that routinely assessed histopathologic features in combination with limited biomarkers may provide an informative classification for routine use.


METHODS
Hierarchical cluster analysis based on components of histopathologic grade (tubule formation, nuclear pleomorphism, and mitotic score), expression of ER, cytokeratin 5/6, and HER2 amplification identified four breast cancer subgroups in a cohort of 270 cases. Cluster subgroup membership was compared with observed and Adjuvant! Online predicted 10-year survival. Survival characteristics were confirmed in an independent cohort of 300 cases assigned to cluster subgroups using a decision tree model.


RESULTS
Four distinct breast cancer cluster subgroups (A-D) were identified that were analogous to molecular tumor types and showed a significant association with survival in both the original and validation cohorts (P < 0.001). There was a striking difference between survival for patients in cluster subgroups A and B with ER(+) breast cancer (P < 0.001). Outcome for all tumor types was well estimated by Adjuvant! Online, with the exception of cluster B ER(+) cancers where Adjuvant! Online was too optimistic.


CONCLUSIONS
Breast cancer subclassification based on readily accessible pathologic features could improve prognostic assessment of ER(+) breast cancer.
Webster
Lucy R
LR
Translational Oncology, Sydney West Area Health Service, Westmead, NSW, Australia.
Lee
Shu-Fen
SF
Ringland
Clare
C
Morey
Adrienne L
AL
Hanby
Andrew M
AM
Morgan
Graeme
G
Byth
Karen
K
Mote
Patricia A
PA
Provan
Pamela J
PJ
Ellis
Ian O
IO
Green
Andrew R
AR
Lamoury
Gillian
G
Ravdin
Peter
P
Clarke
Christine L
CL
Ward
Robyn L
RL
Balleine
Rosemary L
RL
Hawkins
Nicholas J
NJ
D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000378:metabolism*; D001943:Breast Neoplasms / Q000145:classification / Q000378:metabolism* / Q000473:pathology*; D018270:Carcinoma, Ductal, Breast / Q000145:classification / Q000378:metabolism / Q000556:secondary; D018275:Carcinoma, Lobular / Q000145:classification / Q000378:metabolism / Q000556:secondary; D016000:Cluster Analysis; D015331:Cohort Studies; D005260:Female; D005784:Gene Amplification; D020869:Gene Expression Profiling; D006801:Humans; D007124:Immunoenzyme Techniques; D017404:In Situ Hybridization, Fluorescence; D053547:Keratin-14 / Q000378:metabolism; D053555:Keratin-5 / Q000378:metabolism; D053553:Keratin-6 / Q000378:metabolism; D008207:Lymphatic Metastasis; D008875:Middle Aged; D009367:Neoplasm Staging; D009376:Neoplasms, Hormone-Dependent / Q000145:classification / Q000378:metabolism / Q000473:pathology; D020411:Oligonucleotide Array Sequence Analysis; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism; D011960:Receptors, Estrogen / Q000378:metabolism*; D011980:Receptors, Progesterone / Q000378:metabolism; D015996:Survival Rate
D014408:Biomarkers, Tumor; D053547:Keratin-14; D053555:Keratin-5; D053553:Keratin-6; D018719:Erb-b2 Receptor Tyrosine Kinases; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone